Various types of biometric systems are used more and more in order to provide for increased security and/or enhanced user convenience.
In particular, fingerprint sensing systems have been adopted in, for example, consumer electronic system and devices, thanks to their small form factor, high performance, and user acceptance.
Among the various available fingerprint sensing principles, such as capacitive, optical, thermal etc., capacitive sensing is most commonly used, in particular in applications where size and power consumption are important issues.
All capacitive fingerprint sensors provide a measure indicative of the capacitance between each of several sensing structures and a finger placed on or moved across the surface of the fingerprint sensor. If a fingerprint is going to be measured a drive signal is required in the capacitive fingerprint sensor to excite a change in potential difference between the finger and the sensing structure.
As capacitive fingerprint sensing devices are required to detect ever smaller capacitive differences in order to accurately capture a fingerprint image, the influence of noise in the sensor is becoming increasingly important. In particular, the fingerprint sensing device is particularly sensitive to externally injected common mode noise. Typically, this type of noise can be injected to the fingerprint sensor through a charger connected to a device in which the fingerprint sensor is located. Moreover, common mode noise can have a large spread in frequency, amplitude and shape. The injected common mode noise signal can make the system ground to swing in reference to the finger thereby looking like an additional drive signal. This results in corrupt measurements and poor image quality.
The negative impact of common mode noise can be suppressed or filtered by implementing various noise reduction techniques. One example of a technique for common mode noise suppression is to take the average of a number of digital readings from each pixel to reduce the influence of noise. However, analog to digital conversion is time consuming and it is not desirable to increase the time it takes to capture a fingerprint image. Alternatively, or in combination, it is possible to use post-processing methods which runs through the captured fingerprint image and tries to subtract characteristic common mode noise. However, a disadvantage of this method is that measurement values might be corrupted in case of saturation during the analog sampling, in which case it may be difficult or impossible to cancel the influence of noise.
Accordingly, there is a need for an improved method and capacitive fingerprint sensing device for efficiently detecting and handling noise.